AI products need better taste, not more magic
The durable advantage in AI will come from judgment: choosing what the model should do, when it should act, and how it earns trust.
AI demos are optimized for surprise. Products are optimized for repeat use.
The difference between those two things is taste: the thousands of small decisions that turn raw capability into something understandable, reliable, and worth returning to.
Start with the human loop
Before choosing a model, map the human loop. What is someone trying to accomplish? Where do they hesitate? What context do they already have? Which mistakes are cheap, and which ones destroy trust?
The best AI interaction is rarely “a chatbot for everything.” It is a thoughtful division of labor between the person and the system.
Use AI to:
- Compress a slow first pass
- Reveal structure hidden in messy information
- Offer several credible directions
- Handle repetitive transformation
- Notice patterns a person can judge
Keep the person close to moments involving identity, consequence, and taste.
Confidence should be designed
AI interfaces need to communicate what happened, where the answer came from, and what the user can change. A beautifully worded result with invisible assumptions is still a weak product.
Trust grows when a system makes its work legible.
The model is not the experience
Models will keep improving and converging. Product judgment compounds differently. The team that understands a specific customer, owns the workflow, and develops a recognizable point of view can build value that survives the next model release.
Capability gets attention. Taste earns a place in someone’s life.